Wednesday, 15 August 2018
Just relax and you'll get pregnant? Meta-analysis examining women's emotional distress and the outcome of assisted reproductive technology☆
Social Science & Medicine Volume 213, September 2018, Pages 54-62 Social Science & Medicine Review article Author links open overlay panelJenniferNicoloro-SantaBarbaraCheyanneBussoAnneMoyerMarciLobel Department of Psychology, Stony Brook University, 100 Nicolls Road, Stony Brook, NY, 11794-2500, USA Received 18 January 2018, Revised 14 June 2018, Accepted 24 June 2018, Available online 27 June 2018. crossmark-logo https://doi.org/10.1016/j.socscimed.2018.06.033 Get rights and content Highlights • Anxiety prior to infertility treatment is not associated with pregnancy outcome. • Depressive symptoms pre-treatment are not associated with pregnancy outcome. • Perceived stress pre-treatment is not associated with pregnancy outcome. • Anxiety and depressive symptoms during treatment are not associated with outcomes. Abstract Rationale Couples worldwide are seeking treatment for infertility in growing numbers. Both infertility and its treatment are stressful experiences that generate considerable emotional distress. There is speculation that women's distress is associated with poorer likelihood of pregnancy via assisted reproductive technology (ART) and plausible psychobiological mechanisms bolster this association, although prior reviews of existing evidence find little support. A rigorous, comprehensive, and up to date analysis of research on the association of women's distress with ART outcomes is imperative. Objective We systematically searched for and analyzed evidence regarding the association of women's distress before and during treatment with the likelihood of treatment success via ART. Method Meta-analysis using a random-effects model was conducted on prospective studies (k = 20) that compared levels of anxiety, depressive symptoms, or perceived stress before or during ART treatment in women who achieved successful pregnancy outcomes versus those who did not (total N = 4308). Results Anxiety, depressive symptoms, or perceived stress pre-treatment, and anxiety or depressive symptoms during treatment, were not associated with less favorable ART outcomes. Prior treatment experience, age, and duration of infertility were not significant moderators of these associations. No eligible studies examined perceived stress during treatment. Conclusion Results cast doubt on the belief that distress impedes the success of infertility treatment, offering hope and optimism to the many women who feel emotionally responsible for the outcome of ART and informing the evidence-based practices of their health-care providers. We also identify specific areas and research methods needed to corroborate and extend study conclusions, including study of factors that elevate or attenuate distress in women undergoing infertility treatment. Previous article in issue Next article in issue Keywords Infertility Anxiety Depressive symptoms Stress Assisted reproductive technology Pregnancy Women 1. Introduction Nearly 70 million partnered women of reproductive age worldwide, including 1.5 million in the U.S., are infertile, defined as not being able to conceive after one year of unprotected intercourse (Boivin et al., 2007; Chandra et al., 2013; Fathalla, 1992). Many people associate being female with the ability to conceive and bear a child. Thus, infertility can leave a woman feeling different, defective, or out of step with her peers. Infertility can also disrupt a woman's life goals and result in loneliness (Kavlak and Saruhan, 2002), powerlessness, and stigmatization (Cousineau & Domar, 2007). Additionally, infertile women may experience grief, anger, sadness, bodily disparagement, lack of femininity, shame, or self-blame (Benyamini et al., 2009; Frederiksen et al., 2015). The experience can be traumatic for some (Benyamini et al., 2005; Klonoff-Cohen et al., 2001; Merari et al., 2002). Assisted reproductive technology (ART) has become an increasingly common treatment for infertility. About half of all infertile women in developed or developing countries will seek such treatment (Boivin et al., 2007). The most common types of ART are in-vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI). Although ART can be life changing for some women in helping them conceive a child (Klonoff-Cohen, 2008), the process is often physically demanding and may entail frequent blood tests, ultrasounds, daily hormone injections, laparoscopic surgery, and surgery to retrieve oocytes (Demyttenaere et al., 1991; Klonoff-Cohen, 2008; Klonoff-Cohen & Natarajan, 2004). Infertility treatment is also expensive. Costs vary worldwide (Collins, 2002), with the average cost of an IVF cycle in the U.S. ranging between $10,000 to $15,000 (depending on insurance coverage and patient characteristics; Society for Assisted Reproductive Technology, 2017a) to half of an individual's annual income in some countries (Collins, 2002). Furthermore, such expensive treatments do not guarantee success. In Europe, for example, the reported pregnancy rate for IVF is 34.5% (European IVF-Monitoring Consortium et al., 2016). In the U.S., the singleton live birth rate for a cycle of IVF in 2014 was 52.6% for women under 35 years old and declined with age, to a low of 6.7% for women older than 42 (Society for Assisted Reproductive Technology, 2017b). Many couples cease treatment because of the intensity of strain they experience (Domar, 2004; Domar et al., 2010; Smeenk et al., 2004), even when there is a high likelihood of success and sufficient financial resources to cover the cost (Brandes et al., 2009; Domar, 2004). The most common reasons cited for discontinuing treatment include emotional distress (Domar, 2004; Domar et al., 2010) across all stages of treatment (Gameiro et al., 2012) and adverse impact on the partner relationship (Domar, 2004). Not surprisingly, the uncertainty of ART has been shown to increase symptoms of depression in women (Seibel, 1997; Dunkel-Schetter and Lobel, 1991). Research has shown that all stages of treatment can be distressing. Before treatment, a woman may be coping with the chronic stressor of being infertile (Domar et al., 1993; Stanton et al., 1992) and, in some cases, she may be considering ART as her last chance to have a biological child (Seibel, 1997). Before treatment, some women experience fear, uncertainty, and emotional, religious, or moral dilemmas about the treatment itself. Additionally, waiting for a pregnancy result, receiving a negative pregnancy test result, waiting to hear about fertilization, and the wait between IVF treatment attempts are extremely stressful time points once treatment has begun (Laflont and Edelman, 1994). Many women report they are exhorted by family and friends as well as by the popular media to “just relax and then you will conceive” (Bouchez, 2005). This belief is perpetuated by anecdotes of infertile women who conceive after going on a vacation or after ceasing treatment and deciding to adopt a child (Wischmann, 2003). The self-blame created from the idea that a woman's emotional distress is somehow responsible for treatment failure only adds to the anguish experienced by many women during this experience (Gameiro, 2016). 1.1. Distress and reproductive functioning A number of plausible psychobiological pathways are implicated in the possibility that a woman's distress affects her fertility or can impede the success of infertility treatment (Toufexis et al., 2014; Whirledge and Cidlowski, 2010). These pathways involve both the hypothalamic pituitary adrenal (HPA) axis, which regulates the stress response, and the hypothalamic pituitary gonadal (HPG) axis, which regulates reproduction (Massey et al., 2016). Psychological stressors are known to activate the HPA axis, resulting in elevated levels of glucocorticoids. Acute elevation in glucocorticoids is adaptive as this stress hormone prioritizes survival by preparing for the fight or flight response (Sayers, 1950). However, chronically high levels of glucocorticoids can impair fertility by adversely affecting ovarian and uterine functioning (Whirledge and Cidlowski, 2013), interfering with the length of the luteal phase and the timing of ovulation, and reducing the likelihood of implantation and early pregnancy maintenance (Nakamura et al., 2008). The impact of distress on reproductive outcomes might also occur through health behaviors. There is compelling evidence that people under high stress take poorer care of themselves and are more likely to engage in health-impairing behaviors such as smoking and other substance use (Ng and Jeffery, 2003; Stetson et al., 1997). Such health behaviors can hamper the success of infertility treatment. Domar et al. (2015) found that women undergoing IVF who use drugs and alcohol, smoke cigarettes, and drink caffeine adversely influence their IVF cycle. Distress may also affect a woman's ability or willingness to comply with treatment regimens (Lopes et al., 2014). In fact, Gameiro et al.’s (2012) a systematic review found that the psychological burden of IVF treatment was the most cited reason for non-compliance. 1.2. Distress and assisted reproductive technology outcome Some evidence suggests that there is a direct association between an infertile woman's distress and her reduced likelihood of pregnancy with ART, including ICSI and IVF, although other studies have not found this association. Four systematic, narrative, or meta-analytic reviews of this research yielded somewhat different conclusions (Boivin et al., 2011; Klonoff-Cohen, 2005; Massey et al., 2014; Matthiesen et al., 2011). In a systematic review of 51 prospective and retrospective studies, Klonoff-Cohen (2005) examined the association of lifestyle factors such as stress with in vitro fertilization and perinatal outcomes (e.g., birthweight, gestational age, multiple gestations) and concluded that there is limited evidence for an association between stress and unfavorable IVF outcomes. However, Klonoff-Cohen also noted that this conclusion is not definitive due to the heterogeneity in studies. This review is the only one to examine associations of health behaviors such as smoking and caffeine and alcohol use with outcomes of IVF. Klonoff-Cohen concluded that there is substantial evidence to corroborate a relationship between smoking and IVF outcomes, but an insufficient number of studies examining alcohol and caffeine use to draw conclusions about the impact of these behaviors. Boivin et al. (2011) conducted a meta-analysis of 14 prospective studies examining the association of distress before the start of treatment with the IVF outcome of clinical pregnancy after one cycle. Boivin et al. included studies that examined trait anxiety, state anxiety, or depression and combined state and trait anxiety scores to calculate an aggregate effect size; when anxiety and depression were reported in the same study, the authors gave priority to anxiety. Their results indicated no association of anxiety or depression before the start of infertility treatment with treatment outcome. To examine moderation, these authors also performed subgroup analyses on the timing of emotional distress, history of ART, and composition of the not pregnant group, which were all non-significant. Matthiesen et al. (2011) identified 31 studies that examined the association of stress, state anxiety, trait anxiety, or depression before and during treatment with assisted reproductive technology outcomes including serum pregnancy test, clinical pregnancy, live birth, number and quality of oocytes harvested, number and quality of embryos transferred, fertilization rates, and implantation rates. However, there were too few studies to quantitatively evaluate all of these outcomes, so Matthiesen et al.’s meta-analysis included only studies examining serum pregnancy, clinical pregnancy, or live births. The results yielded small but statistically significant associations of stress, trait anxiety, and state anxiety separately with negative clinical pregnancy rates. Matthiesen et al. also conducted meta-regressions that indicated duration of infertility was a significant moderator of the association of state anxiety and depression with outcomes. For both types of distress, longer duration was associated with reduced chance of clinical pregnancy. ART status was a significant moderator of state anxiety with anxious inductees experiencing worse outcomes than anxious veterans, and age was a significant moderator of depression, such that depression was associated with reduced chance of clinical pregnancy for younger women. In the only review assessing biological markers of stress, Massey et al. (2014) conducted a systematic review of eight studies examining the association between cortisol and IVF outcomes including number of oocytes retrieved, oocyte cleavage, oocyte fertilization rates, miscarriage rates, and clinical pregnancy. They found mixed evidence for the relationship of cortisol with these IVF outcomes: for example, four studies reported that lower cortisol was associated with establishment of clinical pregnancy whereas three studies reported that higher cortisol levels were associated with pregnancy. Additionally, Massey et al. highlighted methodological weaknesses in the existing literature. The contradictory findings from these reviews are attributable in part to the heterogeneity of individual studies evaluated because of different inclusion/exclusion criteria used. There are also substantial differences in the methods of the reviews themselves, including operational definitions and statistical treatment of the distress variables. For example, Matthiesen et al. (2011) assessed trait anxiety, state anxiety, depression, or stress separately, whereas Boivin et al. (2011) included studies that examined trait anxiety, state anxiety, or depression and combined effect sizes for these, giving priority to anxiety when trait or state anxiety was measured in conjunction with depression in the same study. As the prevalence of women who use infertility treatment and especially IVF continues to grow, and given the scientific plausibility that distress can affect the success of infertility treatment, there is a pressing need to update and re-examine available research and investigate the existence and magnitude of association between distress and infertility treatment outcomes in a methodologically rigorous manner. 2. The present investigation To redress the limitations of prior reviews and provide rigorous analysis of available research, including studies conducted since the publication of prior reviews, we conducted a literature search and meta-analytic review to examine the association of infertile women's distress with the outcome of IVF and ICSI treatment. Associations with distress both before and during treatment were examined as previous research suggests that these time periods may be associated with different risks for women undergoing IVF. Studies were reviewed that operationalized distress by assessing state anxiety, depression, or stress (perceived general stress, infertility related stress, or occupational stress). This review improved upon prior research in several ways. First, we used well-defined study inclusion/exclusion criteria: any study that involved treatment with an assisted reproductive technology (IVF and ICSI) was eligible. Second, we used a more rigorous and informative outcome, verified pregnancies, than has been used in prior reviews. Third, to operationally define emotional distress, we included studies that assessed state anxiety, depression, or stress. We did not include studies of trait anxiety as some prior reviews have done (e.g., Boivin et al., 2011; Matthiesen et al., 2011). Dispositional variables such as trait anxiety may affect reporting of stressful events (Pluess et al., 2010) and thus influence the observed association between distress and the outcome of ART. Furthermore, as a dispositional characteristic, we would expect trait anxiety to be quite stable and therefore not a good indicator of women's emotional distress associated with ART. Combining distress variables as prior studies have done also obscures their distinct contributions. Examining all three constructs individually, as we do in this review, provides a more fine-tuned analysis of women's emotional states and allows for the possibility that the magnitude of association with treatment outcome may differ for these types of distress. 3. Method 3.1. Search methods A search of electronic databases PubMed, Scopus, and PsycINFO was conducted for articles published between 1977 and December 2017 using the following search terms: [psychological stress OR distress OR anxiety OR depression OR stress] AND [in-vitro fertilization OR assisted reproductive technology OR IVF OR assisted reproduction OR intracytoplasmic sperm injection OR ICSI OR assisted reproductive techniques] AND outcomes. MeSH terms were used in PubMed. General terms like “assisted reproductive technologies” were used in order to capture a wide variety of infertility studies. Additionally, the reference lists of all identified articles, and of two previous meta-analyses (Boivin et al., 2011; Matthiesen et al., 2011) and two systematic reviews (Klonoff-Cohen, 2005; Massey et al., 2014) were carefully examined for potential studies. The result was 660 potential articles. Inspection of abstracts and full texts resulted in 41 potentially eligible articles based on 39 independent studies (see Fig. 1). Fig. 1 Download high-res image (534KB)Download full-size image Fig. 1. Study selection. 3.2. Selection criteria and data extraction Studies were eligible if they were published in a peer-reviewed journal or as a dissertation, used a prospective design with a distress variable quantitatively assessed with a validated instrument in female participants before the start of infertility treatment or during treatment, and reported the outcome (pregnant/not pregnant) after a cycle or multiple cycles of treatment with an assisted reproductive technology (IVF and ICSI). Additionally, to be eligible, pregnancy outcome needed to be determined by clinical evidence of HCG levels, ultrasound confirmation of embryo heartbeat, or live birth, and results needed to include an effect size or include metrics that could be used to calculate an effect size (e.g., sample mean and standard deviation). Authors of 19 potentially eligible studies were contacted because their articles did not include information needed to calculate an effect size; two authors responded to the request for necessary information. When multiple articles were published using the same sample, one article per sample was chosen randomly and included in the analysis (e.g., An et al., 2011; An et al., 2013; Smeenk et al., 2001; Verhaak et al., 2001). On the basis of these criteria, 20 studies were included. 3.3. Distress constructs and measures When multiple distress variables were reported (e.g., anxiety and depression) in the same study, they were both evaluated, but in separate analyses. Three studies measuring distress both before the start of treatment and during treatment were included in the analyses. When distress was measured multiple times during the treatment, the time closest to oocyte retrieval was chosen to be included in the analyses as it was the most common time point. 3.3.1. Anxiety Individual studies included in the analysis assessed state anxiety with the State Anxiety subscale of the State-Trait Anxiety Inventory (Table 1; STAI; Spielberger et al., 1983), the Zung Self Rating Anxiety Scale (Zung, 1976), the Psychological General Well Being Index (PGWB; Dupuy, 1984), or The Hospital Anxiety and Depression Scale (Snaith and Zigmond, 1986). All of the studies included reported continuous scores; some also reported quartiles. Table 1. Descriptive information for studies in the meta-analysis. Country N Emotional distress Measure Timing of assessment An et al. (2011) China 264 State anxiety STAI Before treatment & at oocyte retrieval Depressive symptoms C-BDI-II Before treatment & at oocyte retrieval Anderheim et al. (2005) Sweden 139 State anxiety PGWB 1 month before treatment Depressive symptoms PGWB 1 month before treatment Boivin and Takefman (1995) Canada 40 Stress IQ <2 months before the start of treatment State anxiety STAI <2 months before the start of treatment Boivin and schmidt, 2005 Denmark 818 Stress FPI Before the start of treatment de Klerk et al. (2008) Netherlands 289 State anxiety HADS 6 weeks before start of treatment Depressive symptoms HADS 6 weeks before start of treatment Demyttenaere et al. (1992) Belgium 40 Depressive symptoms SDS Day 4 or 5 of cycle Demyttenaere et al. (1998) Belgium 98 Depressive symptoms SDS Day 3 of cycle Ebbesen et al. (2009) Denmark 781 Stress PSS Before start of treatment Depressive symptoms BDI-II Before start of treatment Gourounti et al. (2011) Greece 160 Stress FPI Before start of treatment State anxiety STAI Before start of treatment Depressive symptoms CES-D Before start of treatment Hashemi et al. (2012) Iran 180 State anxiety STAI 1 day before oocyte retrieval Karlidere et al. (2008) Turkey 104 State anxiety STAI 1 day before ET Li et al. (2011) China 107 State anxiety SAS Day of oocyte retrieval Depressive symptoms SDS Day of oocyte retrieval Lintsen et al. (2009) Netherlands 690 State anxiety STAI 1–2 months before treatment; 1 day before oocyte retrieval Depressive symptoms BDI-PC 1–2 months before treatment Lynch et al. (2012) US 214 Depressive symptoms HADS Day 6 of cycle State anxiety STAI Day 6 of cycle Stress PSS Day 6 of cycle Milad et al. (1998) US 40 State anxiety STAI 13 days after uterine ET Merari et al. (1992) Israel 85 State anxiety STAI Day of oocyte retrieval Depressive symptoms DACL Day of oocyte retrieval Merari et al. (2002) Israel 113 State anxiety STAI 10–15 days before treatment Depressive symptoms DACL 10–15 days before treatment Pasch et al. (2012) USA 202 State anxiety STAI Within the 3 months before treatment Depressive symptoms CES-D Within the 3 months before treatment Visser et al. (1994) Netherlands 65 State anxiety STAI Before the start of treatment Depressive symptoms HSCL Before the start of treatment Verhaak et al. (2001) Netherlands 207 State anxiety STAI 3–10 days before treatment Depressive symptoms BDI-PC 3–10 days before treatment Note. Dashes indicate that information was either not included in the original article or was not provided in a manner that could be coded for the meta-analysis. STAI = State Anxiety subscale of the Spielberger State-Trait Anxiety Inventory; HADS = Hospital Anxiety and Depression Scale; POMS = Profile of Moods States; HSCL = Hopkins Symptom Checklist; IQ = Infertility Questionnaire; PGWB = Psychological General Well-Being Index; DACL = Depression Adjective Checklist; BDI-PC = Beck Depression Inventory for Primary Care; C-BDI-II = Chinese Version of the Beck Depression Inventory; FPI = Fertility Problem Inventory; PSS = Perceived Stress Scale; SAS = Zung Self-Rating Anxiety Scale; SDS = The Zung Self-Rating Depression Scale. 3.3.2. Depression Individual studies included in the analysis assessed depression with the Zung Self-Rating Depression Scale (Table 1; Zung et al., 1965), the Beck Depression Inventory (BDI; Beck and Clark, 1997), the Beck Depression Inventory for Primary Care (BDI-PC; Beck et al., 1997), the Chinese Version of the Beck Depression Inventory (C-BDI-II; The Chinese Behavioral Sciences Society, 2000), or the Depression Adjective Checklist (DACL; Lubin, 1965). All of the included studies reported continuous scores; some also reported clinical cut-offs. Henceforth, for clarity, depression will be referred to as depressive symptoms. 3.3.3. Perceived Stress Individual studies included in the analysis assessed stress with the Perceived Stress Scale (Table 1; Cohen et al., 1983), the Fertility Problem Inventory (Newton et al., 1999), or the Infertility Questionnaire (Bernstein et al., 1985). The latter two instruments are infertility-specific perceived stress measures. 3.4. Data abstraction and statistical analyses Effect sizes were calculated using Comprehensive Meta-Analysis Version 2.0 (Borenstein et al., 2005). The primary outcome measure was the standardized mean difference in anxiety, depressive symptoms, or stress between the group that had treatment success (pregnancy or live birth) and the group that did not. A negative effect size (d < 0) indicates that distress was associated with a reduction in the success of treatment. A random-effects model was used in calculations for the aggregate effect sizes in order to account for variation across individual studies (Borenstein et al., 2009). Due to the interdependency of individual effect sizes, separate meta-analyses were conducted to examine timing of measurement (before the start of treatment vs. during treatment). Two effect sizes were derived for each distress variable except for stress, as there was an insufficient number of studies to calculate an effect size for stress during treatment. Therefore, five effect sizes were examined: anxiety before treatment, anxiety during treatment, depressive symptoms before treatment, depressive symptoms during treatment, and stress before treatment. For each of the aggregate effect sizes, heterogeneity tests were conducted using the Q statistic (Higgins et al., 2003; Lipsey and Wilson, 2001) and the I2 value (Higgins and Thompson, 2002). To explore the possibility that prior treatment experience, age, or duration of infertility may affect the association of distress (state anxiety, depression, and stress) with the outcome of ART, we conducted moderator analyses of ART status (inductee vs. veteran), age, and duration of infertility when effects were significantly heterogeneous, and the number of studies was at least eight. We did not conduct moderator analyses of other participant characteristics because of limited variability of these across studies. Funnel plots (Light and Pillemer, 1984) and rank correlations (Begg and Mazumdar, 1994) were used to evaluate publication bias. The potential impact of any publication bias was assessed using the trim and fill procedure (Duval and Tweedie, 2000). 4. Results As shown in Table 1, sample sizes ranged from 38 to 818, resulting in a total of 4,308 participants with a mean sample age ranging from 29.7 to 36.1 years. Sixteen studies examined state anxiety (12 effect sizes before the start of treatment and seven during), 15 studies examined depressive symptoms (14 effect sizes before the start of treatment and three during), and five studies examined stress (five effect sizes before the start of treatment and zero during). The majority of studies (k = 7) that examined distress during treatment assessed it after one treatment cycle (but before women learned the outcome). Associations of maternal distress with the outcome of infertility treatment are described below for each of the three maternal distress variables at the two time points. The magnitude of aggregate effect sizes is evaluated in terms of Cohen's (1988) recommendations: d ≤ .20, small; d ≥ .50, medium; and d ≥ .80, large. Additional detail about studies included in the analysis appears with supplemental materials. 4.1. Anxiety Forest plots (included with supplemental materials) show the pooled standardized mean differences for anxiety, depressive symptoms, and stress for the two time points between the subsequently successful treatment outcomes versus non-successful treatment outcome groups. For studies examining anxiety before the start of treatment (k = 11), effect sizes ranged from −1.07 to 0.33. Meta-analysis revealed a small, statistically nonsignificant overall effect size of anxiety before the start of treatment on the likelihood of treatment success (d = −0.16, 95% CI = −0.33 to 0.02). Effect sizes were heterogeneous (Q  = 33.10, p < .01, I2 = 69.79, T2 = 0.06). To examine potential moderation by prior infertility treatment (inductee vs. veteran), mixed-effects moderator analysis was conducted using analogue-to-ANOVA for categorical variables. This analysis revealed that prior infertility treatment (Qbetween  = 0.48, p = 0.49) was not a significant moderator of anxiety before treatment in the 11 studies that reported whether participants had been treated for infertility previously. To examine potential moderation by age and duration of infertility, random effects meta-regression analyses were conducted on the ten and eight studies that reported these participant characteristics, respectively. Theses analyses revealed that age and duration of infertility were not significant moderators of anxiety before treatment (slope coefficient = −0.10, SE = 0.05, 95% CI = −0.21 to 0.00, p = 0.05; slope coefficient = 0.09, SE = .10, 95% CI = −0.10 to 0.28, p = 0.38, respectively). Effect sizes for individual studies examining anxiety during infertility treatment (k = 7) ranged from −0.85 to 0.65. There was a small, statistically nonsignificant overall effect size of anxiety during treatment on the likelihood of treatment success (d = −0.10, 95% CI = −0.38 to 0.18). Effect sizes were heterogeneous (Q  = 24.20, p < .01, I2 = 75.21, T2 = 0.10). Moderator analyses were not performed due to the small number of studies eligible for inclusion. 4.2. Depressive symptoms Effect sizes for individual studies examining depressive symptoms before the start of treatment (k = 13) ranged from −2.72 to 0.33. The overall effect size of depressive symptoms before treatment on the likelihood of treatment success was small and statistically nonsignificant (d = −0.15, 95% CI = −0.33 to 0.03). Effect sizes were heterogeneous (Q  = 54.29, p < .01, I2 = 77.90, T2 = 0.08). Mixed-effects moderator analysis was conducted using analogue-to-ANOVA for categorical variables to examine potential moderation by prior infertility treatment. This analysis revealed that prior infertility treatment (Qbetween  = 1.53, p = 0.25) was not a significant moderator of depression before treatment in the 10 studies that reported this variable. To examine potential moderation by age (k = 12) and duration of infertility (k = 10), random effects meta-regression analyses were conducted. These analyses revealed that age and duration of infertility were not significant moderators of depression before treatment (slope coefficient = −0.07, SE = 0.05, 95% CI = −0.17 to 0.03, p = 0.18; slope coefficient = −0.04, SE = 0.08, 95% CI = −0.20 to 0.13, p = 0.67, respectively). Effect sizes for studies examining depressive symptoms during treatment (k = 3) ranged from −0.17 to 0.31. Meta-analysis indicated a small, statistically nonsignificant overall effect size of depressive symptoms during treatment on the likelihood of treatment success (d = −0.05, 95% CI = −0.31 to 0.21). Effect sizes were heterogeneous (Q  = 3.08, p < .22, I2 = 35.02, T2 = 0.02). Moderator analyses were not performed due to the small number of studies. 4.3. Stress Effect sizes for the five studies examining stress before the start of treatment ranged from −1.10 to 0.50. There was a small, statistically nonsignificant overall effect size of stress before the start of treatment on the likelihood of treatment success (d = −0.13, 95% CI = −0.47 to 0.21). Effect sizes were heterogeneous (Q  = 38.26, p < .01, I2 = 89.55, T2 = 0.12). Moderator analyses were not performed due to the small number of studies. 4.4. Publication bias We examined funnel plots for the associations of anxiety, depressive symptoms, and stress before treatment as well as anxiety and depressive symptoms during treatment with the likelihood of treatment success. This revealed some evidence of publication bias; however, all associations had nonsignificant rank correlation tests (Begg and Mazumdar, 1994). To assess whether publication bias influenced the aggregate effect sizes for anxiety, depressive symptoms, and stress before treatment and anxiety and depressive symptoms during treatment, we conducted trim-and fill analyses. Duval and Tweedie's (2000) trim and fill analysis estimates whether there are missing effect size values, imputes the missing values, and then recalculates the aggregate effect size. Using a random effects model, four studies were estimated as missing for anxiety before the start of treatment, with the adjusted aggregate effect size predicted as −0.31, (95% CI = −0.49 to −0.13), three studies were estimated as missing for depression before the start of treatment with the adjusted aggregate effect size predicted as −0.25 (95% CI = −0.43 to −0.07), one study was estimated as missing for stress before the start of treatment with the adjusted aggregate effect size predicted as −0.23 (95% CI = −0.56 to 0.10), and no studies were predicted as missing for anxiety and depressive symptoms during treatment. Together, these results suggest minimal publication bias among the studies included in this review. 5. Discussion The current meta-analysis evaluated research examining the association of infertile women's distress (anxiety, depressive symptoms, and stress) before and during infertility treatment with the success of their treatment. All distress variables were measured independent of each other in the current analyses whereas previous meta-analyses have combined these, obscuring their potentially unique association with infertility treatment outcomes. Women who experience elevated anxiety, depressive symptoms, or stress before treatment and those who experience elevated anxiety or depressive symptoms during treatment were not more likely to have unfavorable ART outcomes. The results corroborate an earlier review that included a subset of studies included in this analysis, but in which anxiety and depression before the start of treatment were collapsed (Boivin et al., 2011). Examining anxiety, depressive symptoms, and stress independently, and separating their effects before and during treatment, enabled us to provide more definitive evidence about their association with the outcome of infertility treatment. Despite persistent beliefs by laypeople and some health care providers that distress reduces the likelihood of pregnancy (as described by Boivin et al., 2011; Gameiro, 2016), beliefs which may persist in part because of their biological and behavioral plausibility (Domar et al., 2015), our results offer scientifically rigorous evidence that controverts such beliefs. How can we resolve these results with the existence of scientifically plausible pathways (psychobiological and behavioral) through which distress could affect ART outcomes? The answer likely involves factors that buffer the effects of distress, including coping, social support, and individual characteristics such as dispositional optimism. Women may be cultivating resilience through the ways that they cope with the stress of infertility and infertility treatment (Domar et al., 1990), through support from friends, family, and healthcare providers (Dunkel-Schetter and Lobel, 1991), by seeking psychotherapeutic help (Frederiksen et al., 2015), and by practicing health behaviors vigilantly (Domar et al., 2015). Such factors have been shown to moderate the impact of emotional distress on other reproductive outcomes (e.g., Lobel et al., 2008) and are likely to operate similarly in the context of infertility. This topic will be important to explore in future investigations. Also needed in future research are tests of more sophisticated models that include factors that may elevate women's distress (Pasch et al., 2012) and factors other than distress which contribute to treatment outcomes. Participant characteristics such as psychiatric and gynecological history, ethnicity, employment status, income, parity, cause of infertility, and number of previous ART attempts have been shown to affect infertility-related distress (e.g., Nicoloro-SantaBarbara et al., 2017) but are not consistently reported or analyzed in studies. Additionally, health behaviors that are often triggered or exacerbated by distress, such as using drugs and alcohol, smoking cigarettes, and drinking caffeine, can adversely influence an IVF cycle (Domar et al., 2015) but are rarely examined. A number of participant characteristics may also affect treatment outcomes directly, such as age and duration of infertility. These are two of the most commonly examined participant characteristics in studies of infertile women, but they tend to have limited variability both within and across existing studies, which may limit the ability to observe their impact on treatment outcome. Of the 18 studies reviewed for this meta-analysis that examined participant age, for example, age predicted poorer IVF outcome in only a minority of studies (Boivin and Schmidt, 2005; Ebbesen et al., 2009; Gourounti et al., 2011; Karlidere et al., 2008; Lynch et al., 2012; Merari et al., 2002; Pasch et al., 2012). Duration of infertility was a significant predictor of poorer outcome in only one of the nineteen studies which examined this variable (Boivin and schmidt, 2005). Nine studies examined a related variable, the number of previous IVF attempts. Only two found that it predicted poorer outcomes (Anderheim et al., 2005; Boivin and schmidt, 2005). To explore the possibility that prior treatment experience, age, or duration of infertility may have influenced the association of distress with outcomes, we conducted moderator analyses of these for distress variables that had been examined in at least eight studies. Prior treatment experience, age, and duration of infertility did not significantly moderate anxiety or depression before treatment. However, meta-analysis is most powerful in testing moderators when there is a large number of effect sizes, so these moderator analyses were too underpowered to reliably examine the impact of such participant characteristics. This is reinforced by the mixed pattern of results that has emerged from prior meta-analyses examining moderation. Boivin et al. (2011), for example, did not find evidence of moderation by timing of emotional distress or by history of ART. Matthiesen et al. (2011) reported that duration of infertility was a significant moderator of the association of state anxiety and depression with outcomes, that ART status was a significant moderator of state anxiety only, and that age was a significant moderator of depression. Notably, some of these analyses were based on a small number of studies, in some cases as few as six. Although we could not perform additional moderator analyses due to inconsistent reporting of potential moderators in individual studies, we qualitatively reviewed the participant characteristics that were reported, and we observed that location of the study seemed to produce the only meaningful pattern. That is, all of the studies that yielded significant effects were conducted outside the United States. The countries where studies with significant findings were conducted (e.g., Denmark, Turkey, and Israel) have universal access to healthcare. Currently in the U.S., only 15 states mandate insurance coverage for infertility treatment (RESOLVE, 2018) and the expense of treatment varies by insurance provider and by state. Whether healthcare differences affect associations of distress with treatment outcomes remains to be examined rigorously, although it is clear that the costs of healthcare for treatment of infertility can themselves cause distress (Dyer and Patel, 2012), not only in the U.S., but around the world, especially in resource-poor countries. Apart from differences in healthcare, social factors such as national and cultural differences in the status of women, expectations about childbearing, and attitudes toward infertility (Bell, 2016; Benyamini et al., 2017) may also affect the experience of ART. The consequences of infertility vary across cultures. In some, childlessness is associated with low status, violence, or ostracism (Greil, 1997; Rutstein and Shah, 2004; World Health Organization, 2002), and may diminish future economic security (Cousineau & Domar, 2007). 5.1. Study strengths, limitations, and implications for research Although the effect sizes reported here were small and not statistically significant, the majority of effect sizes were in favor of an association between distress and reduced likelihood of pregnancy. It is possible that this study did not detect an effect of distress during treatment due to the limited number of eligible studies that examined distress during this period. Additionally, although we were able to differentiate studies that examined emotional distress before the start of treatment from studies that assessed emotional distress during treatment, there was variability in the individual studies' timing of assessment. Although distress during treatment was most commonly measured near oocyte retrieval, this measurement time point ranged from one day before oocyte retrieval to 13 days' post embryo transfer. Similarly, the measurement period of distress before treatment ranged from within three months of treatment to Day 6 of menstrual cycle. It is possible that specific processes that occur during a narrow window of time during the treatment period (e.g., ovarian stimulation, oocyte retrieval, embryo transfer, and pregnancy testing) are more affected by emotional distress than others, a possibility that could not be examined with the limited number of studies currently available. Approximately a decade after Verhaack et al. (2007) identified a need for “comprehensive, consistent knowledge about the course of the emotional response through various stages and cycles of [ART] treatment” (p. 33), there remains a need for repeated assessments of distress at uniform time points throughout infertility treatment. Another important methodological challenge for future studies is to identify the particular types of distress that might impair fertility or impede treatment. Infertility-specific distress measures have been found to be more sensitive at detecting emotional and behavioral reactions to infertility compared to general distress measures (Benyamini et al., 2008; Boivin, 2003; Newton et al., 1999) and it is possible that infertility-specific distress has greater impact on fertility than does more general or non-specific types of distress. Studies of specific forms of distress relevant to other reproductive health experiences such as pregnancy have proven especially powerful in predicting physiological, behavioral, and health outcomes (Alderdice et al., 2012). Of the five stress effect sizes, the only significant effects were from studies that used an infertility-specific measure, the Fertility Problem Inventory (Boivin and schmidt, 2005; Gouronti et al., 2011). None of the studies in this review used infertility-specific anxiety or depression measures. 6. Conclusions Stress related to infertility has received growing attention over the past decade (Society for Reproductive Technologies, 2014). There is a large emotional and financial investment in infertility treatment for individuals and society. However, systematic, scientifically rigorous research on psychosocial factors associated with infertility treatment outcomes has been sparse. The present systematic review and meta-analysis evaluates current, scientifically robust research and highlights the types of studies that are still needed. Results clarify and offer careful analysis indicating that women's emotional distress does not appear to be detrimental to the success of treatment through ART. However, there is a pressing need to alleviate distress associated with infertility, infertility treatment, and treatment failure (Pasch et al., 2012). Developing and delivering psychological interventions that focus on stress management and coping skills training may help reduce the considerable personal, familial, and societal impact of infertility and its treatment. Targeting the psychological burden associated with infertility treatment on women and on their partners–who are often not the focus of this research–may enable couples to remain in treatment and help allay their distress (Pasch et al., 2012). What is at stake for many women and their partners is the ability to fulfill their vital life goals of bearing and raising children. Appendix A. Supplementary data The following are the supplementary data related to this article: Download Word document (45KB) Help with doc files SUPPLEMENTAL Table 2. SUPPLEMENTAL Fig. 2 Download high-res image (618KB)Download full-size image SUPPLEMENTAL Fig. 2. SUPPLEMENTAL Fig. 3 Download high-res image (580KB)Download full-size image SUPPLEMENTAL Fig. 3. 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